Deep Learning GPU Training System (DIGITS)

4.2
(3)

NVIDIA Deep Learning GPU Training System (DIGITS) deep learning for data science and research to quickly design deep neural network (DNN) for image classification and object detection tasks using real-time network behavior visualization.

Work for Deep Learning GPU Training System (DIGITS)?

Learning about Deep Learning GPU Training System (DIGITS)?

We can help you find the solution that fits you best.

Deep Learning GPU Training System (DIGITS) Reviews

Chat with a G2 Advisor
Write a Review
Filter Reviews
Filter Reviews
  • Ratings
  • Company Size
  • Industry
Ratings
Company Size
Industry
Showing 3 Deep Learning GPU Training System (DIGITS) reviews
LinkedIn Connections
Deep Learning GPU Training System (DIGITS) review by Robert G.
Robert G.
Validated Reviewer
Review Source
content

"digging deep into Nvidia sytems"

What do you like best?

what I like best it that you can interactively train models using Tensorflow which is helpful , I can mangage data easily. overall a great product

What do you dislike?

i really don't have any dislikes, i just started using the program

Recommendations to others considering the product

I recommend a better user friendly interface , but we just started the program so we will see if it will work for us in the longrun

What business problems are you solving with the product? What benefits have you realized?

biggest plus factors compared to a GPU is that we have a fully standalone chip that does not need to have a CPU with our main system memory attached to it

Sign in to G2 to see what your connections have to say about Deep Learning GPU Training System (DIGITS)
Deep Learning GPU Training System (DIGITS) review by G2 User
G2 User
Validated Reviewer
Review Source
content

"Good for beginners"

What do you like best?

Ability to see how the networks train in real time. Inference, with visualization of each feature map and layer response. Easy generation of datasets and models.

What do you dislike?

Poor documentation. Difficulty to add new layers. Only works in 2D. Difficult to install.

What business problems are you solving with the product? What benefits have you realized?

Medical image analysis problems, mostly segmentation. The learning curve is quite easy.

What Artificial Neural Network solution do you use?

Thanks for letting us know!
Deep Learning GPU Training System (DIGITS) review by G2 User in Insurance
G2 User in Insurance
Validated Reviewer
Review Source
content

"Great product "

What do you like best?

Works seemlessly with our training interface and the programming made for ease for the software team

What do you dislike?

Nothing really from a programing standpoint and its just easy

Recommendations to others considering the product

Nope

What business problems are you solving with the product? What benefits have you realized?

Training systems that work. The ease of use made our IT team work for faster deployment of training programs

There are not enough reviews of Deep Learning GPU Training System (DIGITS) for G2 to provide buying insight. Below are some alternatives with more reviews:

1
Keras Logo
Keras
4.7
(13)
Keras is a neural networks library, written in Python and capable of running on top of either TensorFlow or Theano.
2
Mocha Logo
Mocha
4.0
(13)
Mocha is a Deep Learning framework for Julia, inspired by the C++ framework Caffe that is efficient implementations of general stochastic gradient solvers and common layers, it could be used to train deep / shallow (convolutional) neural networks, with (optional) unsupervised pre-training via (stacked) auto-encoders.
3
AWS Deep Learning AMIs Logo
AWS Deep Learning AMIs
4.2
(11)
The AWS Deep Learning AMIs is designed to equip data scientists, machine learning practitioners, and research scientists with the infrastructure and tools to accelerate work in deep learning, in the cloud, at any scale.
4
TFLearn Logo
TFLearn
4.0
(5)
TFlearn is a modular and transparent deep learning library built on top of Tensorflow that provide a higher-level API to TensorFlow in order to facilitate and speed-up experimentations, while remaining fully transparent and compatible with it.
5
ConvNetJS Logo
ConvNetJS
4.1
(4)
ConvNetJS is a Javascript library for training Deep Learning models (Neural Networks) entirely in a browser.
6
Torch Logo
Torch
4.0
(3)
Torch is a scientific computing framework with wide support for machine learning algorithms that puts GPUs first.
7
julia-ann Logo
julia-ann
3.3
(3)
julia-ann is the implementation of backpropagation artificial neural networks in Julia that allow users to build multilayer networks and accept DataFrames as inputs. fit! and predict currently require Float64 matrices and vectors.
8
Knet Logo
Knet
4.5
(3)
Knet (pronounced "kay-net") is a deep learning framework implemented in Julia that allows the definition and training of machine learning models using the full power and expressivity of Julia.
9
brain Logo
brain
4.3
(3)
brain is a JavaScript neural network library to recognize color contrast.
10
NeuralTalk2 Logo
NeuralTalk2
4.3
(2)
NeuralTalk2 is an Efficient Image Captioning code in Torch that runs on GPU
Show more
Kate from G2

Learning about Deep Learning GPU Training System (DIGITS)?

I can help.
* We monitor all Deep Learning GPU Training System (DIGITS) reviews to prevent fraudulent reviews and keep review quality high. We do not post reviews by company employees or direct competitors. Validated reviews require the user to submit a screenshot of the product containing their user ID, in order to verify a user is an actual user of the product.